Architecture Repository
Write-ups, projects, and the notes I take chasing certifications.
A working archive of how things are designed and why. Posts are one-off write-ups. Series dig into a larger topic across multiple posts.
50 posts
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Hot, Warm, and Cold Data Paths on Azure
Splitting incoming data by how fast results are needed, and where Azure Stream Analytics fits — data streams, event processing, and the three formats it accepts.
☰ Part of Azure Data Services: SQL, Cosmos DB, and Analytics -
Azure Data Lake Storage, Databricks, and Synapse
What a data lake is on Azure, how Databricks and Synapse sit on top of it, and where Microsoft Fabric now fits — including the Data Lake versus Blob Storage comparison that no longer holds.
☰ Part of Azure Data Services: SQL, Cosmos DB, and Analytics -
Azure Data Factory and Integration Runtimes
How Data Factory orchestrates ETL across disparate stores — pipelines, activities, datasets, linked services, and data flows — and which of the three integration runtimes an on-premises source requires.
☰ Part of Azure Data Services: SQL, Cosmos DB, and Analytics -
Azure Managed Redis and Caching Patterns
Azure Cache for Redis is retiring and Azure Managed Redis replaces it — the four new tiers, what changes for a migration, and the caching patterns worth knowing whichever service you're on.
☰ Part of Azure Data Services: SQL, Cosmos DB, and Analytics -
Azure Table Storage vs Cosmos DB for Table
Two services share one table data model and the same SDK operations, but differ on latency guarantees, throughput ceilings, indexing, and global distribution — here's which side of that line a workload belongs on.
☰ Part of Azure Data Services: SQL, Cosmos DB, and Analytics -
Azure Cosmos DB: APIs, Request Units, and Availability
Choosing a Cosmos DB API and capacity mode, how availability scales from single-region to multi-write, and the cost multipliers that come with each step up in redundancy.
☰ Part of Azure Data Services: SQL, Cosmos DB, and Analytics -
Azure SQL Purchasing Models: DTU vs vCore
Choosing between the DTU and vCore purchasing models, what the serverless compute tier changes about billing, and why DTU costs the same whether or not anyone uses the database.
☰ Part of Azure Data Services: SQL, Cosmos DB, and Analytics -
Azure SQL: Database, Managed Instance, or Virtual Machine
The three Azure SQL deployment options and what actually separates them — instance-scoped features, OS-level access, and administrative overhead — plus the high availability options each one does and doesn't support.
☰ Part of Azure Data Services: SQL, Cosmos DB, and Analytics -
Azure Data Storage: Managed vs Unmanaged Strategies
How to classify data before choosing a service, and what moving from a self-managed database to a managed one actually buys you — high availability, scaling, threat detection, and auto-tuning you'd otherwise build yourself.
☰ Part of Azure Data Services: SQL, Cosmos DB, and Analytics -
System Design Primer: A Tour of Scalability Fundamentals
A condensed walkthrough of Donne Martin's open-source System Design Primer. The core trade-offs behind scalable systems and the building blocks: DNS, CDNs, load balancers, database replication and sharding, caching, message queues.